Evaluation of Disease Activity of Systemic Lupus Erythematosus by D-dimer Combined with Red Blood Cell Distribution Width.

BACKGROUND: To investigate the value of D-dimer combined with red blood cell distribution width (RDW) in evaluating the disease activity of systemic lupus erythematosus (SLE). METHODS: A total of 105 SLE patients confirmed in our hospital from July 2018 to September 2020 were collected as the SLE group, and 60 healthy persons matched in age and gender during the same period were collected as the control group. According to the SLEDAI score, SLE patients were divided into SLE active group and SLE inactive group, and RDW and D-Dimer levels were detected. RESULTS: The level of RDW in the SLE active group [14.8 (13.4, 16.8)] was significantly higher than that in the SLE inactive group [13.4 (12.6, 14.37)] and control group [12.3 (12, 12.7)], with statistically significant differences (p < 0.05). The D-dimer level in the SLE active group was 1.36 (0.9, 2.25) mg/L, which was significantly higher than that in SLE inactive group [0.34 (0.22, 0.52)] mg/L and control group [0.15 (0.08, 0.19)] mg/L, with statistically significant differences (p < 0.05). Both RDW and D-dimer were positively correlated with the SLEDAI score (r = 0.393, p = 0.000), (r = 0.483, p = 0.000). The results of receiver operating characteristic curve showed that the area under the curve of RDW and D-Dimer alone was 0.875 and 0.954, respectively, while the area under the curve of RDW combined with D-Dimer was the largest, 0.984. CONCLUSIONS: The levels of RDW and D-dimer are closely related to the disease activity of SLE patients, and RDW combined with D-dimer is more valuable in assessing the disease activity of SLE patients.

[Study on the differentially expressed genes of steroid-resistant and steroid-sensitive nephrotic syndrome].

OBJECTIVE: To identify the genes differentially expressed among the steroid-resistant nephrotic syndrome (SRNS), steroid-sensitive nephrotic syndrome (SSNS) and normal children, and understand the molecular mechanism of SRNS. METHODS: Affymetrix microarray technology was used to obtain such a profile. The differentially expressed genes among these groups were identified based on signal-to-noise ratios by GCOS software; real-time PCR analysis was performed to confirm the microarray results. RESULTS: There were 157 genes differentially expressed among these groups. The genes up-regulated both in SRNS and SSNS were involved primarily in ionic transportation, immuno-signal transduction and apoptosis. In particular, CLNS1A gene was down regulated in SRNS but up regulated in SSNS. CONCLUSION: Several differentially expressed genes, such as CLNS1A and HLA-DRB4 were found to be closely related to the pathogenesis of SRNS and SSNS. This DNA microarray analysis has provided some important clue to the molecular mechanism of SRNS.